docs: def _reorient_3d(image):
      """
      Reorganize the data for a 3d nifti
      """
      # Create empty array where x,y,z correspond to LR (sagittal), PA (coronal), IS (axial) directions and the size
      # of the array in each direction is the same with the corresponding direction of the input image.
      new_image = numpy.zeros([image.dimensions[image.sagittal_orientation.normal_component],
                               image.dimensions[image.coronal_orientation.normal_component],
                               image.dimensions[image.axial_orientation.normal_component]],
                              dtype=image.nifti_data.dtype)
  
      # Fill the new image with the values of the input image but with matching the orientation with x,y,z
      if image.coronal_orientation.y_inverted:
          for i in range(new_image.shape[2]):
              new_image[:, :, i] = numpy.fliplr(numpy.squeeze(image.get_slice(SliceType.AXIAL,
                                                                              new_image.shape[2] - 1 - i).original_data))
      else:
          for i in range(new_image.shape[2]):
              new_image[:, :, i] = numpy.fliplr(numpy.squeeze(image.get_slice(SliceType.AXIAL,
                                                                              i).original_data))
  
      return new_image